Construction of an STK11 Mutation and Immune-Related Prognostic Prediction Model in Lung Adenocarcinoma.

IF 1.6 4区 生物学 Q4 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Bo Tang, Xia Zhao, Hongbing Liu, Qingfeng Zhang, Kui Liu, Xiaoyan Yang, Yun Huang
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引用次数: 0

Abstract

Background: STK11 mutation in LUAD affects immune cell infiltration in tumor tissue, and is associated with tumor prognosis.

Objective: This study aimed to construct a STK11 mutation and immune-related LUAD prognostic model.

Materials and methods: The mutation frequency of STK11 in LUAD was queried via cBioPortal in TCGA and PanCancer Atlas databases. The degree of immune infiltration was analyzed by CIBERSORT analysis. DEGs in STK11mut and STK11wt samples were analyzed. Metascape, GO and KEGG methods were adopted for functional and signaling pathway enrichment analysis of DEGs. Genes related to immune were overlapped with DEGs to acquire immune-related DEGs, whose Cox regression and LASSO analyses were employed to construct prognostic model. Univariate and multivariate Cox regression analyses verified the independence of riskscore and clinical features. A nomogram was established to predict the OS of patients. Additionally, TIMER was introduced to analyze relationship between infiltration abundance of 6 immune cells and expression of feature genes in LUAD.

Results: The mutation frequency of STK11 in LUAD was 16%, and the degrees of immune cell infiltration were different between the wild-type and mutant STK11. DEGs of STK11 mutated and unmutated LUAD samples were mainly enriched in immune-related biological functions and signaling pathways. Finally, 6 feature genes were obtained, and a prognostic model was established. Riskscore was an independent immuno-related prognostic factor for LUAD. The nomogram diagram was reliable.

Conclusion: Collectively, genes related to STK11 mutation and immunity were mined from the public database, and a 6-gene prognostic prediction signature was generated.

Abstract Image

Abstract Image

Abstract Image

肺腺癌STK11突变及免疫相关预后预测模型的构建
背景:LUAD中STK11突变影响肿瘤组织免疫细胞浸润,与肿瘤预后相关。目的:构建STK11突变与免疫相关的LUAD预后模型。材料和方法:通过cbiopportal在TCGA和PanCancer Atlas数据库中查询LUAD中STK11的突变频率。采用CIBERSORT分析免疫浸润程度。分析STK11mut和STK11wt样品中的DEGs。采用metscape、GO和KEGG方法对DEGs进行功能分析和信号通路富集分析。将免疫相关基因与deg重叠,获得免疫相关deg,采用Cox回归和LASSO分析构建预后模型。单因素和多因素Cox回归分析验证了风险评分与临床特征的独立性。建立nomogram预测OS。同时引入TIMER分析6种免疫细胞浸润丰度与LUAD特征基因表达的关系。结果:STK11在LUAD中的突变频率为16%,野生型和突变型STK11免疫细胞浸润程度不同。STK11突变和未突变LUAD样品的deg主要富集于免疫相关的生物学功能和信号通路。最终获得6个特征基因,并建立预后模型。风险评分是LUAD的独立免疫相关预后因素。nomogram diagram是可靠的。结论:总的来说,从公共数据库中挖掘出与STK11突变和免疫相关的基因,并生成了6个基因的预后预测特征。
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来源期刊
Iranian Journal of Biotechnology
Iranian Journal of Biotechnology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
CiteScore
2.60
自引率
7.70%
发文量
20
期刊介绍: Iranian Journal of Biotechnology (IJB) is published quarterly by the National Institute of Genetic Engineering and Biotechnology. IJB publishes original scientific research papers in the broad area of Biotechnology such as, Agriculture, Animal and Marine Sciences, Basic Sciences, Bioinformatics, Biosafety and Bioethics, Environment, Industry and Mining and Medical Sciences.
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